ClearTK 2.0: Design patterns for machine learning in UIMA S Bethard, P Ogren, L Becker – Proceedings of the Ninth International …, 2014 – lrec-conf.org … Since its inception in 2008, ClearTK has been adopted by multiple developers worldwide in both academia and indus- try (including University of Colorado, Technische Univer- sität Darmstadt, Apache cTAKES, Thomson Reuters, and 3M) and has been employed on diverse … Cited by 8 Related articles

TIDA: A Spanish EHR Semantic Search Engine R Costumero, C Gonzalo, E Menasalvas – 8th International Conference on …, 2014 – Springer … see Figure 1) presents the following components: a DB as common data storage system with all hospital’s data, from reports to images and patient’s structured information which will serve information to the immediate upper level of components; the Mayo/Apache cTAKES as free … Cited by 1 Related articles All 3 versions

Panel: Clinical Natural Language Processing in Languages Other Than English A Névéol, H Dalianis, G Savova, P Zweigenbaum – perso.limsi.fr … 2014). Integrating languages other than English in Apache cTAKES Apache cTAKES (ctakes.apache.org) has been quite successful in assembling and sustaining a global community of developers and users of state-of-the-art English language clinical NLP. … Related articles All 2 versions

Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record C Lin, EW Karlson, D Dligach… – Journal of the …, 2014 – jamia.oxfordjournals.org … For features, Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) was used to extract standard vocabulary from relevant sections of the unstructured clinical narrative. … The DocTimeRel model was released as part of Apache cTAKES. … Cited by 1 Related articles All 5 versions

Concept selection for phenotypes and disease-related annota-tions using support vector machines N Collier, A Oellrich, T Groza – Proc. PhenoDay and …, 2014 – phenoday2014.bio-lark.org … In this paper, we investigate the utility of four existing conceptual coding pipelines (ie MetaMap [13], Apache cTAKES [14], NCBO annotator [15] and BeCAS [16]) in order to identify and harmonise the phenotypes and other concepts related to the diagnosis and treatment of … Cited by 1 Related articles

Disease Template Filling using the CTAKES YTEX Branch JD Osborne – ceur-ws.org … The base system employed was the YTEX branch of ctakes, specifically revision 1588688 at https://svn.apache.org/repos/asf/ctakes/branches/ytex. Default set- tings were used for YTEX, including a concept window length of 10. The 2013AB version of UMLS was used. … Related articles

A broad-coverage collection of portable NLP components for building shareable analysis pipelines RE de Castilho, I Gurevych – Proceedings of the Workshop on …, 2014 – anthology.aclweb.org … purpose. The Apache cTAKES project (Savova et al., 2010) offers a UIMA-based pipeline for the analysis of medical records which includes components from ClearNLP, OpenNLP, and more for the basic language analysis. These … Cited by 18 Related articles All 7 versions

ThinkMiners: Disorder Recognition using Conditional Random Fields and Distributional Semantics A Parikh, A PVS, J Mustafi, L Agarwalla, A Mungi – SemEval 2014, 2014 – aclweb.org … BIO representation means the 1https://ctakes. apache. org/ words in the text are assigned one of the follow- ing tags B-begin, I-inside and O-outside of the entity ie in this case a disorder. So now the task of NER is a sequence labeling problem to assign the labels to the tokens. … Cited by 1 Related articles All 9 versions

Discovering body site and severity modifiers in clinical texts D Dligach, S Bethard, L Becker… – Journal of the …, 2014 – jamia.oxfordjournals.org … result replication we make the gold standard corpus we used in our experiments available to the research community, and release our best-performing methods open source as part of the Apache clinical Text Analysis and Knowledge Extraction System28 (cTAKES)29 allowing … Cited by 8 Related articles All 12 versions

Sophia: a expedient UMLS concept extraction annotator G Divita, QT Zeng, AV Gundlapalli… – AMIA Annual …, 2014 – ncbi.nlm.nih.gov … clinical text. Among them, cTAKES and HITex are well represented in the field. MetaMap … KnowledgeMap 10 . Many of these efforts are built upon two frameworks adopted or developed for use within the NLP field: GATE 11 and Apache-UIMA. A … Cited by 2 Related articles All 4 versions

Automating Data Abstraction in a Quality Improvement Platform for Surgical and Interventional Procedures M Yetisgen, P Klassen, P Tarczy-Hornoch – EGEMS, 2014 – ncbi.nlm.nih.gov … Some systems (MedLEE) are proprietary and others (cTAKES, HiTEX) rely on third party frameworks like Apache UIMA and GATE, which we felt required too much time and effort to extend and customize to accommodate our particular data and system requirements. … Related articles All 6 versions

Comparing MMTx and a Lucene-based Lookup Module to Extract Drug Concepts From Clinical Documents JC Thibault, SM Meystre – researchgate.net … LULU is an aggregation of the following UIMA components: a tokenizer, a POS tagger, a chunker, and the Lucene wrapper presented above. The tokenizer is a modified version of the cTAKES tokenizer. … 2. Apache. UIMA (Unstructured Information Management Architecture). … Related articles

UIMA Ruta Workbench: Rule-based Text Annotation PKM Toepfer – COLING 2014, 2014 – anthology.aclweb.org … upon UIMA are the DeepQA system Watson (Ferrucci et al., 2010) and the clinical Text Analysis and Knowledge Extraction System (cTAKES)(Savova et … UIMA Ruta is developed by an active community1 and is released like UIMA under the industry-friendly Apache License 2.0. … Cited by 1 Related articles All 6 versions

Disease Name Extraction from Clinical Text Using Conditional Random Fields O Ghiasvand – 2014 – dc.uwm.edu … Some of the tools developed are MedLEE [6], MetaMap [7], and cTAKES [8]. The most recent tools of NER are based on machine … Another team that participated in ShARE/CLEF 2013 NLP challenge, used integrated cTAKES for concept mention detection [15]. … Cited by 2 Related articles All 2 versions

A corpus-based approach for automated LOINC mapping M Fidahussein, DJ Vreeman – Journal of the American …, 2014 – jamia.oxfordjournals.org … The first based on supervised machine learning was created using Apache’s OpenNLP Maxent and the second based on information retrieval was created using Apache’s Lucene. … We used Apache’s Lucene V.3.0.324 to create an information retrieval-based model. … Cited by 3 Related articles All 8 versions

Text mining of cancer-related information: Review of current status and future directions I Spasi?, J Livsey, JA Keane, G Nenadi? – International journal of medical …, 2014 – Elsevier This paper reviews the research literature on text mining (TM) with the aim to find out (1) which cancer domains have been the subject of TM efforts, (2) which. Cited by 12 Related articles All 7 versions

Knowledge-based Extraction of Measurement-Entity Relations from German Radiology Reports O Heiner, B Claudia, Z Sonja… – … (ICHI), 2014 IEEE …, 2014 – ieeexplore.ieee.org … Finally the best entity is selected (8) in dependence of some threshold criteria. 2http://uima.apache. org/ … VII. RELATED WORK Medical text analytics has been conducted in the context of the cTAKES project [13], which is also based on the UIMA framework, and MedLee [14]. … Cited by 1 Related articles All 2 versions